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2. The Application of VISSIM in the Intersection at Grade of Urban Road Nanshaomen Intersection for Example

Author

Lin Yufan and Li Xiaohua

Subjects
Scheme (programming language), Engineering, business.industry, Traffic simulation, Signal timing, Transport engineering, VisSim, Intersection, Line (geometry), business, computer, Traffic bottleneck, computer.programming_language, Computer technology
Abstract

The intersection at grade of urban road is an important part in road system, once the intersection appears traffic jam, the traffic effective operation can be affected. How to improve the capacity of the intersection means very important. Traffic simulation is an effective way to solve traffic problems. It utilizes modern computer technology to realize practical traffic system specialty, analyzes traffic system’s probable action in sorts of limited condition. In this paper, regarding Nanshaomen intersection as studying target, the existing problems in present intersection are found and the reasonable signal timing scheme and traffic lane divider scheme in intersection are put forward with the help of VISSIM, on the basis of investigation the present traffic quantity in peak time, signal timing scheme and traffic lane function divider. The improved scheme is evaluated on motor vehicles travel time, speed, line up length. The result indicates the scheme can reduce the vehicle delay and improve the capacity of the intersection effectively, and the application of VISSIM in the intersection at grade of urban road can get to good effect. It provides the effective reference to solve increasingly serious traffic jam in the intersection at grade of urban road.

Published
2010

6. Stimulus Design for Visual Evoked Potential Based Brain-Computer Interfaces.

Author

Xu H, Hsu SH, Nakanishi M, Lin Y, Jung TP, and Cauwenberghs G

Subjects
Humans, Photic Stimulation methods, Electroencephalography methods, Neurologic Examination, Algorithms, Evoked Potentials, Visual, Brain-Computer Interfaces
Abstract

Visual stimuli design plays an important role in brain-computer interfaces (BCIs) based on visual evoked potentials (VEPs). Variations in stimulus parameters have been shown to affect both decoding accuracy and subjective perception experience, implying the need for a trade-off in design. In this study, we comprehensively and systematically compared various combinations of amplitude contrast and spectral content parameters in the stimulus design to quantify their impact on decoding performance and subject comfort. Specifically, three parameters were investigated: 1) contrast level, 2) temporal pattern (periodic steady-state or pseudo-random code-modulated), and 3) frequency range. We collected electroencephalogram (EEG) data and subjective perception ratings from ten subjects and evaluated the decoding accuracy and subject comfort rating for different combinations of the stimulus parameters. Our results indicate that while high-frequency steady-state VEP (SSVEP) stimuli were rated the most comfortable, they also had the lowest decoding accuracy. Conversely, low-frequency SSVEP stimuli were rated the least comfortable but had the highest decoding accuracy. Standard and high-frequency M-sequence code-modulated VEPs (c-VEPs) produced intermediates between the two. We observed a consistent trade-off relationship between decoding accuracy and subjective comfort level across all parameters. Based on our findings, we offer c-VEP as a preferable stimulus for achieving reliable decoding accuracy while maintaining a reasonable level of comfortability.

Published
2023
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